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- Publisher Website: 10.1109/CYBER.2018.8688211
- Scopus: eid_2-s2.0-85064964930
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Conference Paper: Content-Based Compressive Sensing
Title | Content-Based Compressive Sensing |
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Authors | |
Issue Date | 2018 |
Publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800486 |
Citation | Proceedings of 2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), Tianjin, China, 19-23 July 2018, p. 379-384 How to Cite? |
Abstract | Compressive sensing (CS)provides an alternative to Shannon/Nyquist sampling theorem by performing signal acquisition and compression simultaneously when the signals are sparse or compressible in certain basis. However, the classical random CS strategy heavily relies on the sparsity of signals under acquisition and fails to reconstruct the signals when they are not sparse. In this paper, we propose an approach to sensing signals based on their content information to reduce the sensing rate and get rid of the sparsity requirement. Experimental results demonstrate the effectiveness of the proposed method for both sparse and non-sparse images. |
Persistent Identifier | http://hdl.handle.net/10722/273051 |
ISSN |
DC Field | Value | Language |
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dc.contributor.author | Li, C | - |
dc.contributor.author | Cheng, Y | - |
dc.contributor.author | Sun, Z | - |
dc.contributor.author | He, P | - |
dc.contributor.author | Bi, S | - |
dc.contributor.author | Xi, N | - |
dc.date.accessioned | 2019-08-06T09:21:38Z | - |
dc.date.available | 2019-08-06T09:21:38Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Proceedings of 2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), Tianjin, China, 19-23 July 2018, p. 379-384 | - |
dc.identifier.issn | 2379-7711 | - |
dc.identifier.uri | http://hdl.handle.net/10722/273051 | - |
dc.description.abstract | Compressive sensing (CS)provides an alternative to Shannon/Nyquist sampling theorem by performing signal acquisition and compression simultaneously when the signals are sparse or compressible in certain basis. However, the classical random CS strategy heavily relies on the sparsity of signals under acquisition and fails to reconstruct the signals when they are not sparse. In this paper, we propose an approach to sensing signals based on their content information to reduce the sensing rate and get rid of the sparsity requirement. Experimental results demonstrate the effectiveness of the proposed method for both sparse and non-sparse images. | - |
dc.language | eng | - |
dc.publisher | IEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800486 | - |
dc.relation.ispartof | IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) | - |
dc.rights | IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER). Copyright © IEEE. | - |
dc.rights | ©2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
dc.title | Content-Based Compressive Sensing | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Sun, Z: sunzy@hku.hk | - |
dc.identifier.email | Bi, S: shengbi@hku.hk | - |
dc.identifier.email | Xi, N: xining@hku.hk | - |
dc.identifier.authority | Xi, N=rp02044 | - |
dc.identifier.doi | 10.1109/CYBER.2018.8688211 | - |
dc.identifier.scopus | eid_2-s2.0-85064964930 | - |
dc.identifier.hkuros | 300619 | - |
dc.identifier.spage | 379 | - |
dc.identifier.epage | 384 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 2379-7711 | - |